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Carhartt turns to data under new CIO

CIO Business Intelligence

As part of that transformation, Agusti has plans to integrate a data lake into the company’s data architecture and expects two AI proofs of concept (POCs) to be ready to move into production within the quarter. Like many CIOs, Carhartt’s top digital leader is aware that data is the key to making advanced technologies work.

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5 misconceptions about cloud data warehouses

IBM Big Data Hub

The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery. In addition, companies have complex data security requirements.

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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

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Exploring real-time streaming for generative AI Applications

AWS Big Data

You can find similar use cases in other industries such as retail, car manufacturing, energy, and the financial industry. In this post, we discuss why data streaming is a crucial component of generative AI applications due to its real-time nature. For building such a data store, an unstructured data store would be best.

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What Is Data Modernization? 5 Benefits Worth Knowing

Alation

Data modernization is the process of transferring data to modern cloud-based databases from outdated or siloed legacy databases, including structured and unstructured data. In that sense, data modernization is synonymous with cloud migration. With cloud architecture, you’re able to leverage: Elasticity.